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1144 articles for “complexity”
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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Digital Enablers of Nanomedicine: Pharmaceutical Software Across the Lifecycle of Nanotechnology‑Based Drug Products
Abstract: Nanotechnology‑based drug products have rapidly evolved from laboratory concepts to clinically relevant therapies, yet their development is constrained by complex design variables, stringent quality requirements, and emerging regulatory expectations specific to nanomaterials. Pharmaceutical software now plays a central role in the nanomedicine lifecycle, enabling in silico design of nano‑carriers, simulation of nano–bio interactions, control of nanoscale quality attributes during manufacturing, and systematic tracking of safety signals in real‑world use. Integrated …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 11–16 Read article
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The Invisible Engineers: How Viruses Change Cells at the Molecular Level
Abstract: Viruses are frequently thought of as simple parasites, yet at the molecular level, they are quite good at engineering and may change the way the cells they infect work. The Invisible Engineers: How Viruses Rewire Cells at the Molecular Scale looks into how viruses get into host cells, mess up intracellular circuits, and exploit molecular resources to make copies of themselves. This article talks about how viral proteins and nucleic …
Published in International Journal of Virus Studies · Vol. 3, Issue 2, 2026 · pp. 1–6 Read article
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Nano‑Enabled CT for Cancer Imaging: From Molecular Targeting to Image‑Guided Therapy
Abstract: Nano‑enabled computed tomography (CT) exploits high‑atomic‑number (high‑Z) nanomaterials engineered with targeting ligands and therapeutic payloads to enhance contrast, enable molecular imaging, and support image‑guided interventions in oncology. Tumor‑specific nanoprobes such as RGD‑modified gold nanorods, polymer‑coated bismuth nanoparticles, and peptide, antibody, or aptamer‑functionalized platforms can intensify tumor conspicuity, allow early lesion detection and staging, and provide real‑time treatment monitoring. Integration of CT visibility with photothermal, photodynamic, chemo‑, radio‑, and immunotherapeutic functions …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 40–49 Read article
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A Next-Generation IoT-Enabled Smart Cane for the Visually Impaired: Integration of Advanced Navigation, Context-Aware Obstacle Detection, and Real-Time Voice Guidance
Abstract: The rapid growth of Internet of Things (IoT) technologies, combined with advances in embedded systems and artificial intelligence, has opened new possibilities for developing assistive mobility solutions tailored to the needs of individuals with visual impairments. This paper introduces an IoT- enabled smart cane designed to enhance independent mobility through intelligent environmental interpretation and context-aware navigation. Unlike traditional canes that rely solely on tactile feedback, the proposed system incorporates multiple …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 12–17 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Matriarchal Influence and Spiritual Identity: Exploring Women's Spirituality in Young Sheldon
Abstract: The study analyzes the TV series Young Sheldon (2017–2024) through maternal and spiritual feminism. It is a prequel to The Big Bang Theory, set in the 1980s. It is based on a ten-year-old Sheldon’s struggles to adjust to his environment. It aims to examine the study critically, emphasizing the role of his mother and her maternal and spiritual practices through episodes of seasons one to five. The study works on …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 33–43 Read article
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A Review on Digital Twin Technology in Robotics
Abstract: Digital Twin (DT) technology has emerged as a transformative concept in robotics and automation, enabling virtual representation of physical systems, real-time monitoring, and performance optimization. This review explores the foundations of Digital Twin, its integration in robotic systems, key enabling technologies, applications, current challenges, and future research directions. The paper concludes by highlighting how Digital Twin transforms design, control, prediction, and human-robot collaboration.Digital Twin technology is transforming the field of …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
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Intelligent Earth: AI As A Catalyst For Climate Action
Abstract: Artificial Intelligence (AI) is assuming an increasingly influential role in climate science, providing advanced tools capable of interpreting vast, complex, and multi-dimensional environmental datasets. Traditional climate modeling approaches, while grounded in physical principles, frequently struggle to deliver high-resolution, real-time, and region-specific forecasts because of heavy computational demands, incomplete observations, and uncertainties in representing small -- scale processes. Artificial intelligence (AI) techniques, especially machine learning and deep learning, provide strong substitutes …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 1, 2026 · pp. 48–52 Read article
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A Review on: Cotard’s Syndrome
Abstract: Cotard’s Syndrome is a rare and severe mental health condition characterized by nihilistic delusions, in which individuals firmly believe that they are dead, no longer exist, or that parts of their body are decaying or missing. These beliefs are not symbolic or metaphorical but are experienced as absolute truths, making the disorder particularly distressing and difficult to manage. The syndrome is most commonly observed in association with major depressive disorder, …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 1, 2026 · pp. 5–9 Read article
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Role of Pharmaceutical Software in Vaccine Development and Manufacturing Process Optimization
Abstract: Vaccine development and manufacturing have become increasingly complex due to the emergence of diverse vaccine platforms, stringent regulatory expectations, and global demand for safe and effective immunization. Across the vaccine lifecycle – from antigen design and preclinical evaluation to large‑scale manufacturing and post‑marketing surveillance – pharmaceutical software now plays a central role in handling data, optimizing processes, and ensuring regulatory compliance. Software tools support in silico antigen and epitope design, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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A study on Parametric and Non-Parametric Statistical Tools
Abstract: This research report provides a brief overview of the most recent research techniques. The field of the research process has seen a resurgence of attention due to recent advancements in academia. Professors, Ph.D. candidates, researchers, investigative officers, and university students comprise the demographic of this research article. The article will become an essential part of your research papers, projects, and reports for citations due to future obligations. This study is …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 10–31 Read article
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Advanced Water Purification Techniques for Sustainable Clean Water Management: A Comprehensive Review
Abstract: The growing global demand for safe drinking water, coupled with increasing pollution from industrialization, urbanization, and agricultural activities, has intensified the need for efficient and sustainable water purification technologies. Conventional water treatment processes often fail to remove emerging contaminants such as pharmaceuticals, microplastics, endocrine-disrupting compounds, and heavy metals. Advanced water purification technologies—including membrane filtration, advanced oxidation processes (AOPs), nanotechnology-based adsorbents, photocatalysis, electrochemical treatment, and bio-inspired purification systems—have emerged as promising …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 47–52 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Thermodynamic Irreversibility in Semen Transport
Abstract: Sperm ejaculation is a vital reproductive process that involves both complex biological functions and energetic mechanisms. Beyond the physiological aspects, thermodynamics offers a framework to analyze energy conversion, exergy use, and irreversibility during sperm activity. ATP provides the main source of exergy for motility, but part of this energy is inevitably lost as heat and entropy generation, reflecting inefficiencies in the process. Because heat regulation directly affects metabolic rates, motility …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 Read article
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Epigenetic Modifications in Health, Disease, and Precision Therapeutics (From Genome to Epigenome)
Abstract: Introduction: Epigenetic alterations play a crucial role in regulating gene expression in both normal physiological and disease states. These reversible modifications—such as DNA methylation, histone acetylation, phosphorylation, ubiquitination, and chromatin remodelling—are increasingly implicated in complex diseases including cancer and neurodegenerative disorders. Despite advances in standard therapeutic approaches, patient responses remain variable, largely due to genetic heterogeneity and epigenetic dysregulation. This highlights the need for incorporating epigenetic understanding into personalized medicine. …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Vaccines Through Time: Conventional Foundations and Next-Gen Innovations–Part 1
Abstract: Vaccination serves as a critical pillar of global public health, markedly decreasing infection rates and associated mortality. Traditional vaccine platforms such as live attenuated, inactivated, toxoid, and subunit vaccines have demonstrated effectiveness against pathogens like Mycobacterium tuberculosis and Plasmodium spp., yet they are constrained by antigenic variability, limited immune persistence, and complex production processes. Breakthroughs in synthetic biology, structural antigen design, and computational vaccinology have driven the development of advanced …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 1, 2026 · pp. 53–70 Read article
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Transforming Rare Disease Diagnosis with AI
Abstract: Artificial intelligence is changing healthcare fast. It is making diagnoses accurate, helping doctors get better results, and streamlining how care works. This paper looks at how AI shows up in healthcare right now – where it is already making a difference, what is working, and what is still tricky. The focus is on machine learning, natural language processing, and computer vision. Particular attention is given to using AI in diagnosing …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Fusion of deep learning autoencoders with random forest for wetland classification using Sentinel-2A data: A case study on Sirpur wetland
Abstract: Present study analyses the performance of deep leaning algorithm-autoencoder to reduce data dimension as compared to conventional models. Classification accuracies of Sirpur wetland using Sentinel 2A dataset with different inputs have also been studied. These inputs sets comprise the reconstructed data through compression of original 13 bands into 4 bands using decoder algorithm, first four Principal Components, all spectral bands, and spectral indices. Random Forest classifier (RF) is used to …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 1, 2026 · pp. 25–35 Read article